Throughout the entire lifecycle of an engineering project, BIM data is primarily generated during the design phase. At this stage, the data gradually evolves from simple to complex, increasing in volume and detail—from basic descriptions in the planning phase to the delivery of comprehensive design models. This data follows strict logical and organizational rules.
An engineering project is an integrated whole, and BIM technology should be applied consistently throughout its implementation. However, in China, BIM is often used directly from the design stage to guide construction and calculate quantities. This approach frequently results in feedback that the models are unusable or the data is inaccurate. These issues do not stem from flaws in BIM technology itself, but rather from differing standards used by various stakeholders to assess BIM’s effectiveness at different project stages.
BIM data generated during the design phase must be effectively transferred to the construction phase to enable BIM’s practical application on-site. Hence, BIM technology should support a complete, end-to-end system, ensuring seamless integration throughout the entire project lifecycle.
The construction industry has entered the era of big data. While construction produces vast amounts of data, much of it remains opaque. As BIM technology continues to advance, integrating BIM with traditional project management will become a key competitive advantage for construction enterprises. This raises the question: what BIM data is involved at each stage of construction?
All digital data generated during construction belongs to engineering data. BIM data during the construction phase primarily consists of two parts: first, the BIM data transferred from the design phase, and second, the data produced by various project participants through different applications during construction. Although design data varies due to differences in design firms, standards, and platforms, it generally forms a structured set of BIM data. When handed over to construction, the data diversifies significantly. The large number of stakeholders and the variety of software tools used to support technical applications generate a wide range of data types with varying organizational structures, including both structured and unstructured engineering data.
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